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Background: Obicetrapib is a next-generation cholesteryl ester transfer protein (CETP) inhibitor. It has emerged as a promising agent for improving lipid parameters and potentially reducing risk of atherosclerotic cardiovascular disease (ASCVD). Methods: A systematic search of databases, including PubMed, Scopus, Embase, Web of Science, Clinical Trials, and Cochrane Library, was conducted to identify relevant randomized controlled trials (RCTs). Outcomes included the assessment of LDL-C reduction, changes in ApoB, non-HDL-C, HDL-C, triglycerides, Lp(a), MACE, as well as the safety and tolerability profile of Obicetrapib in patients with dyslipidemia or ASCVD. Standardized mean differences (SMD) with 95% confidence intervals (CI) were pooled using random-effects. Results: Seven RCTs encompassing 3483 patients were included. Obicetrapib significantly improved lipid parameters. It reduced LDL-C (MSD: –35.43; 95% CI: –40.14 to –30.17; I2 = 93.26%), non-HDL-C (MSD: –36.42; 95% CI: –42.77 to –30.07; I2 = 99.06%), ApoB (MSD: –23.38; 95% CI: –30.68 to –16.08; I2 = 88.56%), and Lp(a) (MSD: –23.95; 95% CI: –35.26 to –12.63; I2 = 77.14%). Obicetrapib also led to a reduction in TG levels (MSD: –0.12; 95% CI: –0.19 to –0.05; I2 = 0.00%). In contrast, favorable increases were observed in HDL-C (MSD: 77.35; 95% CI: 64.56 to 90.13; I2 = 95.82%) and ApoA1 (MSD: 63.93; 95% CI: 53.65 to 74.21; I2 = 81.89%). Despite high heterogeneity, these results support Obicetrapib’s effectiveness in improving atherogenic lipid markers. Obicetrapib demonstrated a safety profile comparable to placebo. The overall risk of any adverse event was slightly reduced in the Obicetrapib group compared to placebo, but the 95% CI included 1, (RR: 0.96; 95% CI: 0.76 to 1.21; I2 = 66.3%; p = 0.01). Specific adverse events such as diarrhea (OR: 1.56; 95% CI: 0.34 to 7.11; I2 = 5.16%; p = 0.57), headache (OR: 1.17; 95% CI: 0.74 to 1.84; I2 = 0.00%; p = 0.50), and back pain (RR: 0.36; 95% CI: 0.11 to 1.16; I2 = 18.3%; p = 0.26) were also not significantly different between groups. Overall, Obicetrapib appears well-tolerated without increased adverse events. Conclusion: Obicetrapib significantly improved lipid parameters, notably reducing LDL-C, non-HDL-C, ApoB, Lp(a), and triglycerides, while increasing HDL-C and ApoA1, with a favorable and comparable safety profile.

Introduction: Patients with variant transthyretin (TTR) amyloid cardiomyopathy (ATTRv-CM) experience early onset disease, rapid progression, and poor outcomes due to amyloid aggregated from destabilized tetrameric TTR. Acoramidis, a highly selective, oral TTR stabilizer, achieves ≥90% TTR stabilization and is approved in the USA, EU, Japan, and UK for adults with wild-type (ATTRwt-CM) or ATTRv-CM. In the phase 3 ATTRibute-CM study and its open-label extension (OLE), acoramidis reduced both the risk of all-cause mortality (ACM) or first cardiovascular-related hospitalization (CVH) through Month 30 and risk of ACM through Month 42 by 36%. Research Question: Is acoramidis efficacy in ATTRv-CM consistent with that observed in the overall ATTRibute-CM population? Methods: In ATTRibute-CM, participants with ATTR-CM were randomized 2:1 to acoramidis HCl 800 mg or PBO, twice daily (BID) for 30 months. After Month 30, all participants enrolled in the OLE received acoramidis HCl 800 mg BID. Genotype (ATTRwt-CM or ATTRv-CM) was captured at randomization; efficacy was analyzed separately in ATTRv-CM. Time-to-event analyses used a stratified Cox model with terms for treatment, baseline 6MWT, genotype, genotype×treatment interaction, stratified by randomization NT-proBNP and eGFR levels. ACM was analyzed at Month 42 (ATTRibute-CM 30 months + OLE 12 months). Results: The ATTRv-CM group comprised 59 patients (39 acoramidis, 20 PBO). Baseline characteristics were mostly similar in both groups ( Table ). The three most common variants reported were p.V142I (n=35), p.I88L (n=7), and p.T80A (n=5). Compared with PBO, acoramidis reduced the risk of ACM/first CVH through Month 30 by 59% (acoramidis, 46.2%; PBO, 75.0%; HR 0.41; 95% CI 0.21–0.81; P =0.011; Fig 1 ) and ACM through Month 42 by 59% (continuous acoramidis, 30.8%; PBO to acoramidis, 60.0%; HR 0.41; 95% CI 0.19–0.93; P =0.032; Fig 2 ) , with Kaplan–Meier curves separating at Months 5 and 10, respectively. Conclusions: In ATTRibute-CM, acoramidis use was associated with clinical benefit in the ATTRv-CM group as demonstrated by a 59% risk reduction in both ACM/first CVH at Month 30, and ACM at Month 42 compared to PBO. These previously unreported findings support the hypothesis that near complete TTR stabilization observed experimentally with acoramidis across multiple TTR mutations translates into improvement in long-term outcomes. Further validation by individual TTR variant is warranted.

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) possess significant therapeutic potential for myocardial regeneration. However, clinical application remains constrained due to the immature phenotype of these cells, which impacts their engraftment as well as their electrical and mechanical integration post-transplantation into the injured heart. In particular, proper alignment of transplanted hiPSC-CMs is essential for synchronous contraction and efficient electromechanical coupling with native tissue. To address this critical clinical challenge, we engineered a tissue patch incorporating aligned electrospun nanofibers designed to enhance hiPSC-CM alignment and promote their structural maturation. Poly(caprolactone) (PCL) nanofibers were fabricated by electrospinning a 10% w/v solution in 1,1,1,3,3,3-hexafluoro-2-propanol at a flow rate of 0.5 mL/h. A voltage of 14 kV was applied to the spinneret and 3kV to the collector, positioned 13 cm away, with additional electrodes to induce fiber alignment. Scanning electron microscopy and ImageJ analysis confirmed fiber diameter and orientation. hiPSC-CMs (1 x 10 6 cells) were seeded onto fiber scaffolds with varied diameters (1.0, 1.5, and 2.0 μm) and densities (low: 20%, moderate: 30%, high: 40%). Among these, 1.5 ± 0.2 μm diameter fibers with a density of 40 ± 3% provided the most effective topographical cues for promoting cell elongation and alignment. Immunofluorescence staining demonstrated that hiPSC-CMs cultured on aligned fibers exhibited enhanced cytoskeletal organization along the fiber axis. Morphological assessment over time showed progressive alignment by day 3. Importantly, hiPSC-CMs cultured on aligned fibers demonstrated stronger and more synchronized contractile activity compared to those cultured on flat glass surfaces. Together, these findings suggest that our aligned nanofiber-based cardiac patch promotes the structural and functional maturation of hiPSC-CMs, highlighting their potential as an advanced platform for improving cardiac cell therapy outcomes.

Introduction/Background: Atrial fibrillation (AF), a common postoperative arrhythmia, is associated with increased morbidity and mortality across various surgical populations. In patients undergoing orthotopic liver transplantation (LT), the presence of AF has been linked to poorer clinical outcomes. However, data on the prognostic significance of new-onset AF during early post-transplant readmissions in orthotopic LT recipients remain limited. Hypothesis: We postulated that incident AF occurring during 90-day post-LT readmissions is independently associated with increased in-hospital mortality, prolonged length of stay, and higher healthcare costs. Methods: We conducted a retrospective cohort study using data from the National Readmission Database (2016–2019). Adult LT recipients (aged >18 years) readmitted within 90 days were identified via ICD-10 coding. Patients who developed new-onset atrial fibrillation (AF) during readmission were compared to those without AF. Primary outcomes included in-hospital mortality, length of stay (LOS), and total hospitalization costs. Multivariable logistic and linear regression models, adjusted for demographic and clinical confounders, were used. Results: Of 31,557 adult LT recipients (mean age 55.5 years, 35% female), 8,449 (27.6%) (mean age 55.3 years, 36.7% women) were readmitted within 90 days. Among those readmitted, 222 patients (2.6%) developed new-onset atrial fibrillation (AF), and 84 (1.0%) died during the readmission period. New-onset AF was associated with a 7.6-fold increased risk of in-hospital mortality (95% CI: 3.0–19.0; P < 0.05). Additionally, AF onset was linked to a mean increase in LOS of 6.2 days (95% CI: 6.2–7.1; P = 0.001) and an average increase in hospitalization costs of $75,396 (95% CI: $11,932–$138,860; P = 0.02). All associations achieved statistical significance. Conclusion(s): New-onset AF during early post-transplant readmissions is associated with significantly worse clinical outcomes and increased healthcare utilization. These findings underscore the need for proactive rhythm monitoring and risk-stratified arrhythmia management during the liver transplant recovery period.

Background: Chronic kidney disease (CKD) has been linked to elevated inflammatory biomarkers, yet few studies have evaluated these associations using iothalamate-based measures of kidney function, highlighting the need for further research. Research question: Is CKD associated with elevated inflammatory markers when defined by measured glomerular filtration rate (mGFR) and urinary albumin-to-creatinine ratio (UACR)? Methods: Participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) cohort were included if they had data available for at least one inflammatory marker at visit 2. 17 inflammatory markers were assessed, including C-reactive protein (CRP), interleukin-6 (IL-6), IL-18, tumor necrosis factor receptors 1 and 2 (TNFR1, TNFR2), serum amyloid A, intercellular and vascular adhesion molecules (ICAM, VCAM), E-selectin, P-selectin, monocyte chemoattractant protein (MCP), myeloperoxidase (MPO), receptor for advanced glycation end products (RAGE), matrix metalloproteinases 2 and 9 (MMP-2, MMP-9), and tissue inhibitors of metalloproteinases 1 and 2 (TIMP-1, TIMP-2). Kindey function was assessed using the urinary clearance of iothalamate. CKD was defined as mGFR < 60 mL/min/1.73 m 2 or UACR ≥ 30 mg/g. To further assess whether associations persisted without albuminuria, we also defined CKD solely by mGFR < 60 mL/min/1.73 m 2 . Generalized estimating equations (GEE) were used to assess associations between CKD status and inflammatory markers, accounting for familial clustering. Exponentiated beta coefficients from GEE models were used to present geometric mean (GM) ratios of each biomarker by CKD status, adjusted for demographics, lifestyle factors, cardiovascular risk factors, and medication use. Results: Among 1,010 participants (mean age 61 ± 10 years; 67% women; 48% Black adults), 207 were classified as having CKD. After adjusting for potential confounders, individuals with CKD had significantly higher levels of hsCRP, VCAM, TNFR1, and TNFR2 compared to those without CKD (GM ratios > 1; p < 0.05), while the remaining inflammatory markers showed no significant differences ( Figure 1 ). Importantly, these elevations remained significant when CKD was defined by mGFR alone ( Figure 2 ). Conclusion: Our findings suggest that CKD, defined by mGFR, is associated with specific inflammatory biomarkers, underscoring the need for mechanistic studies to investigate these associations.

Background: Susceptibility to cardiometabolic diseases (CDs) is shaped by genetic, socio-environmental, and lifestyle factors. We evaluated the associations of disease-specific polysocial risk scores (PSSs)— derived from social determinants of health (SDOH) and lifestyle factors—and genetic risk factors with six CDs, across self-identified race/ethnicity (SIRE) groups in the eMERGE IV cohort. Methods: The six CDs included: atrial fibrillation, coronary heart disease, chronic kidney disease, hyperlipidemia, obesity, and type 2 diabetes. Disease-specific PSSs were developed using machine-learning models based on 65 SDOH and lifestyle factors. Participants were grouped based on their SIRE as Asian, Black, Hispanic/Latino, and White. We evaluated PSS distributions across SIRE groups. Genetic risk was assessed through disease-specific polygenic risk scores (PRSs), monogenic etiologies, and family history (FamHx). High PSS and high PRS were defined as the top 5th percentile. Associations were tested using multivariable logistic regression; model performance was assessed using the C-statistic. Results: Among 20178 participants (50±15 years, 68% female, 40% non-White), the most frequently associated PSS components were physical activity, sleep, self-perceived health, and income. PSS distributions varied across SIRE groups, with Whites having the lowest and Black and Hispanic/Latinos the highest scores for most CDs (Figure 1). All PSSs were significantly associated with their respective CDs, independent of confounders (OR per 1 SD increase: 1.19–2.68; Figure 2-A). No significant interactions were observed between PSSs and PRSs or monogenic etiologies. However, significant interactions were noted between PSSs and FamHx for CKD and obesity. PSS and PRS effects on the odds of CDs were independent (Figure 2-B) and additive (Figure 2-C). Incorporating PSSs into models that included clinical and genetic risk factors improved predictive performance of risk prediction models (Figure 3). Conclusion: PSSs, reflecting socio-environmental and lifestyle disadvantage, varied significantly across SIRE groups and were associated with risk of six CDs, independent of and additive to PRS. Given the substantial variation in socio-environmental and lifestyle risks across SIRE groups, integrating these factors into risk prediction models for CDs may help address health disparities and enhance preventive efforts, especially in marginalized populations.

Background: We investigated the impact of genetic risk factors for coronary heart disease (CHD) -polygenic risk score (PRS), familial hypercholesterolemia (FH), and family history (FamHx)- on CHD risk estimates, across the age spectrum, in two diverse cohorts of US adults -eMERGE IV (eIV) and All of Us (AoU). Methods: CHD was defined as myocardial infarction, unstable angina, and coronary revascularization. Self-identified race/ethnicity (SIRE) was used as a population descriptor. We calculated a PRS for CHD (PRS CHD , PGS004698), ascertained FH as the presence of pathogenic/likely pathogenic variants in FH genes, and defined FamHx as early-onset CHD in first-degree relatives. We employed Pooled Cohort Equations (PCE) to estimate the 10y risk of CHD for adults ≥40y and modeled the association of conventional risk factors with CHD in adults <40y. AoU served as the training set, and eIV as the testing set. We analyzed the impact of PRS CHD and FamHx on CHD risk estimates by a) using multivariable logistic regression and Cox proportional hazard models, assessing discrimination and the extent of risk reclassification; and b) net benefit analysis and decision curves to assess the performance of prediction models across actionable thresholds. Results: We analyzed data for 19348 participants from eIV (age 50±15, 68% female, 41% non-White) and 239645 participants from AoU (age 55±17, 61% female, 48% non-White). Genetic risk factors were significantly associated with CHD. PRS CHD performance varied by SIRE groups, while FamHx was consistent. The effects of PRS CHD and FamHx on CHD were independent and additive (Figure 1). In adults ≥40y, incorporating PRS CHD and FamHx into PCE improved discrimination (C-statistic increased from 0.719 to 0.753; P -diff=9.1×10 -3 , Figure 2) and reclassified risk in 19% and 20% of participants at the 7.5% and 10% 10y CHD risk thresholds, respectively. Between the 7.5% and 10% 10y CHD risk thresholds, incorporating PRS CHD and FamHx into the PCE improved the net benefit of the risk prediction models across White, Black, and Hispanic/Latino groups (Figure 3). Conclusion: PRS CHD and FamHx were independently and additively associated with CHD in two large diverse cohorts in the US. Incorporating PRS CHD and FamHx into PCE improved risk discrimination, reclassified risk in a significant portion of participants, and improved net benefit of the PCE across all three major SIRE groups, motivating the addition of these factors to clinical risk calculators.

Background: Coronary microvascular disease (CMD) may be endothelium-independent (coronary flow reserve, CFR < 2.5) or endothelium-dependent (<50% increase in coronary blood flow in response to acetylcholine). CMD has been implicated in abnormal myocardial relaxation and impaired diastolic function. Wave intensity analysis (WIA) is a hemodynamic method that quantifies the energy of pressure-flow waves driving coronary blood flow. The backward expansion wave (BEW) is the dominant distally originating wave, generated by microvascular suction during ventricular relaxation. Thus, the BEW may offer mechanistic insight into the link between CMD and diastolic dysfunction. Hypothesis: We hypothesized that diastolic dysfunction would be more common in patients with CMD, and that the backward expansion wave (BEW) intensity would be lower in those with diastolic dysfunction compared to those without. Methods: Patients with non-obstructive coronary artery disease undergoing invasive coronary physiology assessment of the left anterior descending artery were included (n = 113). Pressure and Doppler flow were recorded at rest, with adenosine, and with acetylcholine for categorization of CMD as endothelium-independent (CMD-Ei) and/or endothelium-dependent (CMD-Ed). Wave intensity analysis was used to calculate cumulative BEW (J×m -2 ) at rest in CMD, CMD-Ei (endothelium-independent), and CMD-Ed (endothelium-dependent) subgroups. Diastolic dysfunction was diagnosed by transthoracic echocardiogram using the 2016 American Society of Echocardiography (ASE) guidelines. Results: Of the 113 study patients, 88 (77.9%) had CMD and 25 (22.1%) did not. Among those with CMD, 39 patients (44.3%) had diastolic dysfunction (Figure 1). In the patients with CMD, the BEW intensity was significantly lower in patients with diastolic dysfunction compared to those without (6.5 vs. 9.0 × 10 3 W×m -2 ×s -1 , p < 0.05). The same trend was observed for the CMD-Ei (7.2 vs. 9.7 × 10 3 W×m -2 ×s -1 , p < 0.05) and CMD-Ed (6.2 vs. 9.1 × 10 3 W×m -2 ×s -1 , p < 0.05) subtypes. Conclusions: Diastolic dysfunction is frequent in patients with invasively diagnosed CMD. Patients with CMD who have diastolic dysfunction have comparatively lower BEW intensity, regardless of endothelial subtype. Since the BEW is the major driver of coronary flow during diastole, this suggests a mechanism by which CMD may lead to diastolic dysfunction.

Introduction: Diastolic dysfunction is a hallmark of heart failure with preserved ejection fraction, yet echocardiographic grading is challenging in patients with hypertrophic or amyloid cardiomyopathies due to variable structural and functional remodeling. Consequently, there is a need for additional diagnostic tools to identify patients at increased risk of diastolic dysfunction and enhanced filling pressure. Research Question: What is the accuracy of an artificial intelligence (AI)-enabled electrocardiogram (ECG) model to predict diastolic dysfunction in hypertrophic and amyloid cardiomyopathy? Methods: We included patients with diverse phenotypes of hypertrophic cardiomyopathy (HCM) and cardiac amyloidosis and validated Mayo Clinic's AI-enabled ECG model to grade diastolic function (normal: grade 0/1; abnormal: grade 2/3). Echocardiographic analysis of systolic (LVEF) and diastolic function was performed within 14 days of ECG recording. Diastolic function was graded based on E/e’ (>14), left atrial volume index (>34 mL/m2), pulmonary venous atrial reversal flow duration (≥30 ms), and peak tricuspid regurgitation velocity (>2.8 m/s). Filling pressure was considered increased if ≥3 parameters were abnormal, inconclusive if 2 were abnomal, and normal if ≥3 were normal. Echocardiograms with severe mitral regurgitation were excluded. Results: We identified and matched 840 ECGs from non-obstructive HCM patients (n=125, age 58±19y, 70% male), 145 ECGs from obstructive HCM patients (n=29, age 56±18y, 66% male), 225 ECGs from apical HCM patients (n=33, age 66±14y, 61% male), and 382 ECGs from cardiac amyloidosis patients (n=49, age 70±13y, 57% male). The AI-enabled ECG model predicted diastolic dysfunction with an accuracy of 65% (non-obstructive HCM), 67% (obstructive HCM), 65% (apical HCM), and 75% (cardiac amyloidosis), with sensitivities of 94% and 97% for obstructive HCM and cardiac amyloidosis, respectively, and high positive and negative predictive values for cardiac amyloidosis. Systolic dysfunction (LVEF≤40%) was more common in cardiac amyloidosis (29%) than in all HCM patients (5%). Conclusion: The AI-enabled ECG model demonstrates moderate accuracy but high sensitivity for detecting diastolic dysfunction and increased filling pressure, especially in obstructive HCM and cardiac amyloidosis. The AI-enabled ECG is a useful, widely scalable, and low cost tool to identify patients at increased risk for diastolic dysfunction.

Introduction/Background: CHIP is a risk factor for cardiovascular (CV) disease, cancer, and all-cause mortality. Previous work has shown that CHIP, and particularly larger CHIP clones, are associated with adverse CV outcomes, yet the molecular pathways through which CHIP impacts CV risk are poorly defined. Hypothesis/Research Question: We hypothesize that the integration of whole blood transcriptomics and methylomics will provide novel insights into the pathophysiology of CHIP. Methods/Approach: Whole blood DNA methylation profiling, transcriptomics, and whole exome sequencing with CHIP calling for variant allele frequencies (VAF) of ≥2% (CHIP) and ≥10% (large CHIP) were performed for 507 ISCHEMIA and ISCHEMIA-CKD participants with moderate-severe ischemia. We identified transcriptomic and methylomic differences between participants with CHIP and large CHIP vs no CHIP using DESeq2 and limma, adjusted for age, sex, and race/ethnicity. Gene set enrichment analysis (GSEA) and probe set enrichment analysis (PSEA) were performed to identify pathway-level alterations in transcription and methylation, respectively. Results/Data: Clinical characteristics of study participants are described in Fig 1A . Compared to no CHIP (n=391), transcriptomics identified 6 differentially expressed genes (DEGs) in CHIP (n=116) and 27 DEGs in large CHIP (n=35) (p-adj<0.05; abs(logFC)>0.25) (Fig 1B) . Compared to no CHIP, methylation identified no differentially methylated probes in CHIP and 6 in large CHIP (padj<0.20, abs(logFC)>0.03). GSEA identified 137 pathways significantly different in both CHIP and large CHIP vs. no CHIP (padj<0.05), while PSEA identified 724 and 2356 pathways (padj<0.20), respectively. Given its stronger relationship with methylation and transcription, downstream analyses focused on large CHIP. Integrating these data, we found 58 pathways to be both hypomethylated and transcriptionally upregulated in large CHIP, including azurophil granule-related pathways implicated in neutrophil degranulation (Fig 1C) . Further investigation into the gene-probe pairs driving the azurophil granule pathway enrichment in large CHIP revealed hypomethylation and increased transcription of genes implicated in neutrophil extracellular trap formation, including ELANE, PTRN3, AZU1, and CTSG (Fig 1D) . Conclusions: Integration of the methylome and transcriptome suggests large CHIP is linked to neutrophil-mediated immune pathways in patients with stable coronary artery disease.